About this Abstract |
| Meeting |
2026 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2026)
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| Symposium
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2026 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2026)
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| Presentation Title |
Deflated Preconditioned Conjugate Gradient for Accelerating Ill-Conditioned Mechanical and Thermomechanical Process Simulations for Laser Powder Bed Fusion |
| Author(s) |
Dhruba Aryal, Albert C. To |
| On-Site Speaker (Planned) |
Dhruba Aryal |
| Abstract Scope |
Thermomechanical and mechanical process simulations of large parts produced by Laser Powder Bed Fusion (LPBF) remain computationally prohibitive due to large number of time steps. Approaches such as layer-wise and scan track-wise flash heating as well as inherent strain methods, combined with agglomeration techniques, have been developed to reduce temporal resolution requirements. Even with these approximations, simulations of complex geometries and loosely constrained boundary conditions remain expensive, as the dominant bottleneck shifts to the solution of highly ill-conditioned linear systems. This work proposes to develop the Deflated Preconditioned Conjugate Gradient (DPCG) method within a GPU accelerated matrix-free Finite Element Method (FEM) framework with adaptive mesh refinement (AMR) to address these modes in both thermo-mechanical and inherent strain simulations. The proposed method combined with the Inexact Newton Method reduces iteration counts by over 50x – 100x in the problems considered, with increasing gains observed for finer meshes and greater ill-conditioning. |
| Proceedings Inclusion? |
Undecided |